Package: discoCVI
Type: Package
Title: Implementation of the DISCO Metric for Internal Clustering
        Evaluation
Version: 0.1.1
Authors@R: c(
    person("Amin", "Entezari",
           email   = "amin_entezari@outlook.com",
           role    = c("aut", "cre"),
           comment = c(ORCID = "0009-0005-4733-6032")),
    person("Davide", "Chicco",
           email   = "davidechicco@davidechicco.it",
           role    = "ctb",
           comment = c(ORCID = "0000-0001-9655-7142",
                       "Supervision and guidance")),
    person("Anna", "Beer",
           role    = "aut",
           comment = "Original Python implementation (arXiv:2503.00127)"),
    person("Lena", "Krieger",
           role    = "aut",
           comment = "Original Python implementation (arXiv:2503.00127)"),
    person("Pascal", "Weber",
           role    = "aut",
           comment = "Original Python implementation (arXiv:2503.00127)"))
Description: Implementation of the DISCO (Density-based Internal Score for
    Clusterings with nOise) metric, a cluster validity index for evaluating
    density-based clustering results without ground truth labels. DISCO is the
    first index to explicitly assess the quality of noise point assignments in
    addition to cluster quality. It uses density-connectivity distance derived
    from a minimum spanning tree of the mutual-reachability graph, providing
    interpretable, bounded scores in [-1, 1]. Higher scores indicate better
    clustering. Based on Beer et al. (2025)
    <doi:10.48550/arXiv.2503.00127>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 3.6.0)
Imports: FNN, stats
Suggests: dbscan, testthat (>= 3.0.0)
RoxygenNote: 7.3.3
URL: https://github.com/aminentezari/discoCVI
BugReports: https://github.com/aminentezari/discoCVI/issues
NeedsCompilation: no
Packaged: 2026-05-02 08:55:19 UTC; aminentezari
Author: Amin Entezari [aut, cre] (ORCID:
    <https://orcid.org/0009-0005-4733-6032>),
  Davide Chicco [ctb] (ORCID: <https://orcid.org/0000-0001-9655-7142>,
    Supervision and guidance),
  Anna Beer [aut] (Original Python implementation (arXiv:2503.00127)),
  Lena Krieger [aut] (Original Python implementation (arXiv:2503.00127)),
  Pascal Weber [aut] (Original Python implementation (arXiv:2503.00127))
Maintainer: Amin Entezari <amin_entezari@outlook.com>
Repository: CRAN
Date/Publication: 2026-05-05 18:20:13 UTC
Built: R 4.5.2; ; 2026-05-05 21:13:05 UTC; unix
